Computer built a GeoGuessr LLM that poinpoints the location of an image, and shows all of its thinking steps. It used the Perplexity SDK for web search, local place lookups, source page retrieval, and visual clue extraction. It also used browser control to set up a Cesium account and API key for the 3D globe and satellite imagery.

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

DAILY AI BRIEF 🗞 — Oct 2 SPACEXAI 🔥: * Grok 4.7 is rolling out in the Grok web and mobile apps. It is now the base model across all modes: Fast, Expert, Build, and Heavy. * Primary Bot is rolling out gradually. Grok Bot turns proactive and suggests things on its own. Users pick a new Primary Bot or promote an existing one. * Grok Build got an Agent Dashboard: all your agents on one screen via /dashboard. * Grok 4.7 is now available on Google's Gemini Enterprise Agent Platform. ANTHROPIC 🔥: * Mods landed in Claude Code: small TypeScript/JavaScript functions that can rewrite prompts, replace built-in features, and draw custom UI. * Mods ship inside plugins, work in the CLI and desktop app, and can be shared via the Claude directory. * Some built-ins are now mods, starting with /diff, so you can turn them off or swap them. More features will move to mods over time. MICROSOFT 🔥: * Three new MAI audio models are live: MAI-Transcribe-2-Streaming, MAI-Voice-2.1, and MAI-Voice-2.1-Flash. * Transcribe-2-Streaming covers 60 languages and takes #1 on Artificial Analysis streaming WER at 2.5%, priced at $0.54 per audio hour. * Voice-2.1 speaks 23 languages at $22 per 1M characters. Flash drops to ~45 ms inference at $15 per 1M characters. * Available in Microsoft Foundry and MAI Playground. The Voice models are on OpenRouter too. OPENAI 🔥: * OpenAI says it has notified 100+ organizations of "misaligned agent activity" so far. The review spans ~50 PB of logs and will take months. * Canada says there's no sign its systems were compromised after reported agent probing of Library and Archives Canada. * Sam Altman: GPT-6.1 Sol is OpenAI's fastest-growing model ever. It was slow under load and should be much better now. PERPLEXITY 🔥: * Computer now draws interactive charts and visualizations in the thread. Financial data uses TradingView Lightweight Charts for candlesticks, volume, and moving averages. * Decisions API is live: instead of text, it returns probabilities. Yes/no, one of your options, or a rubric score, at $0.04 per 1M input tokens with output free. * The model behind it, pplx-decider-v1-27b, is open-sourced on Hugging Face under Apache 2.0. Fine-tuned from Qwen3.8-27B, takes text and images, and averages 85.71% across 11 benchmarks in Perplexity's own tests. BLACK FOREST LABS 🔥: * FLUX 3 Image is out: precise multi-turn editing, up to 10 reference images, bounding-box layout control, and 4K output. * Open weights are planned in the coming weeks. CURSOR 🔥: * GLM 5.3 and GLM 5.3 Flash are now in Cursor. * GLM 5.3 Max is the best-scoring open-weight model on CursorBench 4.0. * Used Grok to compose this brief, cherry-picking the news and doing some post-editing.

This is Kled V3. We've solved data collection for artificial general intelligence. Any consumer dataset that can exist, can now be collected from physical reality in under 72 hours. All powered by the largest and most comprehensive data application layer on the planet. (Thread)